82 research outputs found

    A Framework for Phasor Measurement Placement in Hybrid State Estimation via Gauss-Newton

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    In this paper, we study the placement of Phasor Measurement Units (PMU) for enhancing hybrid state estimation via the traditional Gauss-Newton method, which uses measurements from both PMU devices and Supervisory Control and Data Acquisition (SCADA) systems. To compare the impact of PMU placements, we introduce a useful metric which accounts for three important requirements in power system state estimation: {\it convergence}, {\it observability} and {\it performance} (COP). Our COP metric can be used to evaluate the estimation performance and numerical stability of the state estimator, which is later used to optimize the PMU locations. In particular, we cast the optimal placement problem in a unified formulation as a semi-definite program (SDP) with integer variables and constraints that guarantee observability in case of measurements loss. Last but not least, we propose a relaxation scheme of the original integer-constrained SDP with randomization techniques, which closely approximates the optimum deployment. Simulations of the IEEE-30 and 118 systems corroborate our analysis, showing that the proposed scheme improves the convergence of the state estimator, while maintaining optimal asymptotic performance.Comment: accepted to IEEE Trans. on Power System

    Optimal Placement of Phasor Measurement Units for Power Systems Using Genetic Algorithm

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    Power grids require monitoring to operate with high efficiency while minimizing the chances of having a failure. However, current monitoring scheme which consists of SCADA (Supervisory Control and Data Acquisition), accompanied with conventional meters distributed throughout the grid, is no longer sufficient to maintain an acceptable operation of the grid. This is evident from the multiple failures and blackouts that happened and are still happening in grids worldwide. This issue became more severe due to systems being operated near their limits (to reduce costs and due to the increase in electricity demands), as well as, the addition of renewable energy sources, which usually have abrupt changes. Smart grids were introduced as a solution to this issue by the inclusion of Wide Area Monitoring System (WAMS), which is mainly based on Phasor Measurement Units (PMU), which are measurement devices that provides synchronized time stamped measurements with high sending rate which significantly improves the monitoring of the grid. However, PMUs are relatively expensive (considering both direct and indirect costs incurred). Thus, it is desired to know the minimum number of PMUs required for achieving certain monitoring criteria. Thus, Optimal PMU Placement (OPP) formulates an optimization problem to solve this issue. In the literature of OPP, multiple objectives and constraints are considered, based on desired criteria. In this thesis, a review of OPP is made, followed by the application of selected algorithms (Integer Linear Programming and Genetic Algorithm) on various test systems as a verification and then applying it to Qatar Grid, to compare between different considerations as well as gain insight about the possible PMU placements for Qatar Grid. The contribution of this thesis is introducing a modified fitness function for the Genetic Algorithm that provides more diverse results than previous papers, while incorporating for various considerations like Zero Injection Buses, Conventional Measurements and current branch limit. It also analyzes the results of current branch limit and provides new plots describing their effects

    Priority Lists for Power System Investments: Locating Phasor Measurement Units

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    Power systems incrementally and continuously upgrade their components, such as transmission lines, reactive capacitors, or generating units. Decision-making tools often support the selection of the best set of components to upgrade. Optimization models are often used to support decision making at a given point in time. After certain time intervals, re-optimization is performed to find new components to add. In this paper, we propose a decision-making framework for incrementally updating power system components. This is an alternative approach to the classical sequential re-optimization decision making for an investment problem with modeled budget constraints. Our approach provides a priority list as a solution with a list of new components to upgrade. We show that i) our framework is consistent with the evolution of power system upgrades, and ii) in particular circumstances, both frameworks provide the same solution if the problem satisfies submodularity property. We have selected the problem of phasor measurement unit localization and compared the solution with the classical sequential re-optimization framework. For this particular problem, we show that the two approaches provide close results, while only our proposed algorithm is applicable in practice. The cases of 14 and 118 IEEE buses are used to illustrate the proposed methodology

    Improved fault-tolerant PMU placement using algebraic connectivity of graphs

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    Due to perpetual and innovative technological advancements, the need for reliable and stable power generation and transmission has been increasing dramatically over the years. Smart grids use advanced technologies to provide self-monitoring, self-checking and self-healing power networks, including smart metering devices capable of providing accurate measurements of the network’s power components. Among the most important metering devices in this context are “Phasor Measurement Units (PMUs)â€. PMUs are metering devices that provide synchronized measurements of voltage, current and phase angle differences using signals from the GPS satellites. However, due to the high cost of such advanced metering devices, studies were performed to determine the minimum number of PMUs required and their strategic placements in the power networks to provide full system observability. In this thesis, we consider fault-tolerant PMU placement aiming to minimize the number of PMUs while maintaining system observability under various contingencies. Conventionally, the optimal number of PMUs in a system is determined based on the system’s connectivity matrix under no contingency. This thesis considers fault- tolerant PMU placement under single and double branch failures. We propose algebraic connectivity, or Fiedler value, to identify the worst- case branch failures in terms of connectivity degradation. The proposed PMU placement accounts for this worst-case and covers a large percentage of other single and double branch failures. Furthermore, we propose the usage of Fiedler vector to provide a PMU placement that would ensure that the system remains fully observable during system partitioning into separate sub-systems. The resulting placements are compared with those obtained without considering connectivity degradation or system partitioning in terms of the percentages of observable systems during any single and double branch failures. The proposed PMU placements have increased percentages of fully observable systems in the event of any single or double branch failures compared to non—contingency based placement, with a reasonable increase in number of PMUs, and for some placement approaches no increase in PMUs is needed for providing a higher percentage of fully observable systems

    Improved fault-tolerant PMU placement using algebraic connectivity of graphs

    Get PDF
    Due to perpetual and innovative technological advancements, the need for reliable and stable power generation and transmission has been increasing dramatically over the years. Smart grids use advanced technologies to provide self-monitoring, self-checking and self-healing power networks, including smart metering devices capable of providing accurate measurements of the network\u27s power components. Among the most important metering devices in this context are Phasor Measurement Units (PMUs) . PMUs are metering devices that provide synchronized measurements of voltage, current and phase angle differences using signals from the GPS satellites. However, due to the high cost of such advanced metering devices, studies were performed to determine the minimum number of PMUs required and their strategic placements in the power networks to provide full system observability. In this thesis, we consider fault-tolerant PMU placement aiming to minimize the number of PMUs while maintaining system observability under various contingencies. Conventionally, the optimal number of PMUs in a system is determined based on the system\u27s connectivity matrix under no contingency. This thesis considers fault- tolerant PMU placement under single and double branch failures. We propose algebraic connectivity, or Fiedler value, to identify the worst- case branch failures in terms of connectivity degradation. The proposed PMU placement accounts for this worst-case and covers a large percentage of other single and double branch failures. Furthermore, we propose the usage of Fiedler vector to provide a PMU placement that would ensure that the system remains fully observable during system partitioning into separate sub-systems. The resulting placements are compared with those obtained without considering connectivity degradation or system partitioning in terms of the percentages of observable systems during any single and double branch failures. The proposed PMU placements have increased percentages of fully observable systems in the event of any single or double branch failures compared to non—contingency based placement, with a reasonable increase in number of PMUs, and for some placement approaches no increase in PMUs is needed for providing a higher percentage of fully observable systems

    A Decision Modeling For Phasor Measurement Unit Location Selection In Smart Grid Systems

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    As a key technology for enhancing the smart grid system, Phasor Measurement Unit (PMU) provides synchronized phasor measurements of voltages and currents of wide-area electric power grid. With various benefits from its application, one of the critical issues in utilizing PMUs is the optimal site selection of units. The main aim of this research is to develop a decision support system, which can be used in resource allocation task for smart grid system analysis. As an effort to suggest a robust decision model and standardize the decision modeling process, a harmonized modeling framework, which considers operational circumstances of component, is proposed in connection with a deterministic approach utilizing integer programming. With the results obtained from the optimal PMU placement problem, the advantages and potential that the harmonized modeling process possesses are assessed and discussed

    Optimal PMU Placement for Türkiye 400 kV Interconnected Power System Observability with Dragonfly Algorithm

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    The Phasor Measurement Unit (PMU) is a modern measuring device built on the system for monitoring, controlling, and protecting power systems. Since the costs of PMU devices are very high, they must be placed in the system in optimum numbers and in a way that monitors the whole system. This study determined the locations and numbers of the optimal number of PMU devices that can monitor the whole system. Integer Linear Programming (ILP) and Binary Particle Swarm Optimization (BPSO) methods are proposed to solve the optimum PMU placement (OPP) problem. Then, the solution to the problem is carried out using Dragonfly Algorithm (DA), which is proposed as a new heuristic method. Solution methods were applied to the IEEE 14-Bus Test System and Türkiye 400 kV Interconnected Power System, and the results were compared. In addition, the results of the proposed methods were compared with the results of different studies in the literature. Thanks to the ILP, BPSO, and DA methods proposed in this study, it has been determined that power systems can be observed with fewer PMU devices. The DA method offers a great cost advantage as it is the method that provides a solution with 5 fewer PMU devices for the 400 kV Interconnected Power System in Türkiye
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